December 2020 arXiv papers — page 68

E. Peik, T. Schumm, M. S. Safronova, A. Pálffy

The low-energy, long-lived isomer in $^{229}$Th, first studied in the 1970s as an exotic feature in nuclear physics, continues to inspire a multidisciplinary community of physicists. Using the nuclear resonance frequency, determined by the strong and electromagnetic interactions inside the nucleus, it is possible to build a highly precise nuclear clock that

William Gropp, Sujata Banerjee, Ian Foster

High Performance Computing (HPC), Artificial Intelligence (AI)/Machine Learning (ML), and Quantum Computing (QC) and communications offer immense opportunities for innovation and impact on society. Researchers in these areas depend on access to computing infrastructure, but these resources are in short supply and are typically siloed in support of their rese

Ren Pang, Zheng Zhang, Xiangshan Gao, Zhaohan Xi

Neural backdoors represent one primary threat to the security of deep learning systems. The intensive research has produced a plethora of backdoor attacks/defenses, resulting in a constant arms race. However, due to the lack of evaluation benchmarks, many critical questions remain under-explored: (i) what are the strengths and limitations of different attack

Rachana Balasubramanian, Samuel Sharpe, Brian Barr, Jason Wittenbach

In the environment of fair lending laws and the General Data Protection Regulation (GDPR), the ability to explain a model's prediction is of paramount importance. High quality explanations are the first step in assessing fairness. Counterfactuals are valuable tools for explainability. They provide actionable, comprehensible explanations for the individual wh

Elizabeth Bradley, Madhav Marathe, Melanie Moses, William D Gropp

Infectious diseases cause more than 13 million deaths a year, worldwide. Globalization, urbanization, climate change, and ecological pressures have significantly increased the risk of a global pandemic. The ongoing COVID-19 pandemic-the first since the H1N1 outbreak more than a decade ago and the worst since the 1918 influenza pandemic-illustrates these matt

Joao H. Quintino Palhares, Yann Beilliard, Fabien Alibart, Everton Bonturim

Resistive switching devices are promising emerging non-volatile memories. However, one of the biggest challenges for resistive switching (RS) memory applications is the device-to-device (D2D) variability which is related to the intrinsic stochastic formation and configuration of oxygen vacancy (VO) conductive filaments. In order to reduce D2D variability, th

Scott A. Yost, Matthew Dittrich, Stanislaw Jadach, B. F. L. Ward

We describe the program KKMC-hh, which calculates Z boson processes in hadronic collisions using coherent exclusive exponentiation (CEEX) with exact second-order photonic corrections at next-to-leading log and first-order weak vertex corrections, including initial and final state photonic radiation and initial-final interference. We describe current applicat

Sander Ø. Hanslin, Alireza Qaiumzadeh

The Dzyaloshinskii-Moriya (DM) interaction plays an essential role in novel topological spintronics, and the ability to control this chiral interaction is of key importance. Developing a general microscopic framework to compute nonequilibrium DM interactions, we theoretically show that the ac electric field component of a laser pulse induces nonequilibrium s

Pedro E. Harunari, Fernando S. Filho, Carlos E. Fiore, Alexandre Rosas

The performance of endoreversible thermal machines operating at finite power constitutes one of the main challenges of nonequilibrium classical and quantum thermodynamics, engineering and others. We introduce the idea of adjusting the interaction time asymmetry in order to optimize the engine performance. We consider one of the simplest thermal machines, com

Michael L. Whittaker, David Ren, Colin Ophus, Yugang Zhang

Clays control carbon, water and nutrient transport in the lithosphere, promote cloud formation5 and lubricate fault slip through interactions among hydrated mineral interfaces. Clay mineral properties are difficult to model because their structures are disordered, curved and dynamic. Consequently, interactions at the clay mineral-aqueous interface have been

T. Washimi, T. Yokozawa, T. Tanaka, Y. Itoh

Environmental noise is one of the critical issues for the observation of gravitational waves, but is difficult to predict in advance. Therefore, to evaluate the adverse impact of environmental noise on the detector sensitivity, understanding the detector response to the environmental noise in actual setup is crucial, for both the observation and future upgra

He Yin, Peter Seiler, Ming Jin, Murat Arcak

A method is presented to learn neural network (NN) controllers with stability and safety guarantees through imitation learning (IL). Convex stability and safety conditions are derived for linear time-invariant plant dynamics with NN controllers by merging Lyapunov theory with local quadratic constraints to bound the nonlinear activation functions in the NN.

Alessio Merlo, Antonio Ruggia, Luigi Sciolla, Luca Verderame

App repackaging refers to the practice of customizing an existing mobile app and redistributing it in the wild to fool the final user into installing the repackaged app instead of the original one. In this way, an attacker can embed malicious payload into a legitimate app for different aims, such as access to premium features, redirect revenue, or access to

Narayan Khadka, Bharat Ratra

We use six different cosmological models to study the recently-released compilation of X-ray and UV flux measurements of 2038 quasars (QSOs) which span the redshift range $0.009 \leq z \leq 7.5413$. We find, for the full QSO data set, that the parameters of the X-ray and UV luminosities $L_X-L_{UV}$ relation used to standardized these QSOs depend on the cosm

Justo Pastor Lambare, Rodney Franco

Counterfactual definiteness is supposed to underlie the Bell theorem. An old controversy exists among those who reject the theorem implications by rejecting counterfactual definiteness and those who claim that, since it is a direct consequence of locality, it cannot be independently rejected. We propose a different approach for solving this contentious issue

Bingchen Liu, Yizhe Zhu, Kunpeng Song, Ahmed Elgammal

Imagining a colored realistic image from an arbitrarily drawn sketch is one of the human capabilities that we eager machines to mimic. Unlike previous methods that either requires the sketch-image pairs or utilize low-quantity detected edges as sketches, we study the exemplar-based sketch-to-image (s2i) synthesis task in a self-supervised learning manner, el

Mauricio Delbracio, Hossein Talebi, Peyman Milanfar

Features obtained from object recognition CNNs have been widely used for measuring perceptual similarities between images. Such differentiable metrics can be used as perceptual learning losses to train image enhancement models. However, the choice of the distance function between input and target features may have a consequential impact on the performance of

L. N. Fletcher, L. Sromovsky, V. Hue, J. I. Moses

The incredible longevity of Cassini's orbital mission at Saturn has provided the most comprehensive exploration of a seasonal giant planet to date. This review explores Saturn's changing global temperatures, composition, and aerosol properties between northern spring and summer solstice (2015-2017), extending our previous review of Cassini's remote sensing i

Mark Connor, Michael O'Neill

The purpose of this research was to compare the robustness and performance of a local and global optimization algorithm when given the task of fitting the parameters of a common non-linear dose-response model utilized in the field of exercise physiology. Traditionally the parameters of dose-response models have been fit using a non-linear least-squares proce

Igor Bandos, Kurt Lechner, Dmitri Sorokin, Paul K. Townsend

Relations between the various formulations of nonlinear p-form electrodynamics with conformal-invariant weak-field and strong-field limits are clarified, with a focus on duality invariant (2n-1)-form electrodynamics and chiral 2n-form electrodynamics in Minkowski spacetime of dimension D=4n and D=4n+2, respectively. We exhibit a new family of chiral 2-form e

Xiang Huo, Mingxi Liu

Existing large-scale optimization schemes are challenged by both scalability and cyber-security. With the favorable scalability, adaptability, and flexibility, decentralized and distributed optimization paradigms are widely adopted in cyber-physical system applications. However, most existing approaches heavily rely on explicit information exchange between a

Tushar Agarwal, Nithin Sugavanam, Emre Ertin

Automatic Target Recognition (ATR) algorithms classify a given Synthetic Aperture Radar (SAR) image into one of the known target classes using a set of training images available for each class. Recently, learning methods have shown to achieve state-of-the-art classification accuracy if abundant training data is available, sampled uniformly over the classes,

L. Máthé, C. P. Onyenegecha, A. -A. Farcaş, L. -M. Pioraş-Ţimbolmaş

The aims of the reported work are to provide new insights into the quantum dot optical properties confined in an inverse of a quadratic Hellmann potential. The Schr\"odinger equation is solved using the Nikiforov-Uvarov (NU) method, in order to obtain the analytical expressions of the eigenenergies and the eigenfunctions. The linear together with the third-o

Ross Shillito, Jonathan A. Gross, Agustin Di Paolo, Élie Genois

The controls enacting logical operations on quantum systems are described by time-dependent Hamiltonians that often include rapid oscillations. In order to accurately capture the resulting time dynamics in numerical simulations, a very small integration time step is required, which can severely impact the simulation run-time. Here, we introduce a semi-analyt

Matteo Agostini, Elisabetta Bossio, Alejandro Ibarra, Xabier Marcano

The Standard Model of Particle Physics predicts the double-$\beta$ decay of certain nuclei with the emission of two active neutrinos. In this letter, we argue that double-$\beta$ decay experiments could be used to probe models with light exotic fermions through the search for spectral distortions in the electron spectrum with respect to the Standard Model ex

Simon Griffiths, Christoph Koch, Matheus Secco

Let the random variable $X\, :=\, e(\mathcal{H}[B])$ count the number of edges of a hypergraph $\mathcal{H}$ induced by a random $m$-element subset $B$ of its vertex set. Focussing on the case that the degrees of vertices in $\mathcal{H}$ vary significantly we prove bounds on the probability that $X$ is far from its mean. It is possible to apply these result

Hao Tang, Xingwei Liu, Kun Han, Shanlin Sun

Multi-organ segmentation is one of most successful applications of deep learning in medical image analysis. Deep convolutional neural nets (CNNs) have shown great promise in achieving clinically applicable image segmentation performance on CT or MRI images. State-of-the-art CNN segmentation models apply either 2D or 3D convolutions on input images, with pros

Sophia A. Henneberg, Stuart R. Hudson, David Pfefferlé, Per Helander

Combined plasma-coil optimization approaches for designing stellarators are discussed and a new method for calculating free-boundary equilibria is proposed. Four distinct categories of stellarator optimization, two of which are novel approaches, are the fixed-boundary optimization, the generalized fixed-boundary optimization, the quasi free-boundary optimiza

J. Pena Gracia, A. Fassatoui, J. Vogel, A. Thiaville

The domain wall dynamics driven by an out of plane magnetic field was measured for a series of magnetic trilayers with different strengths of the interfacial Dzyaloshinskii-Moriya interaction (DMI). The features of the field-driven domain wall velocity curves strongly depend on the amplitude of the HD field stabilising chiral N\'eel walls. The measured Walke

Marc-André Carbonneau, Julian Zaidi, Jonathan Boilard, Ghyslain Gagnon

Learning to disentangle and represent factors of variation in data is an important problem in AI. While many advances have been made to learn these representations, it is still unclear how to quantify disentanglement. While several metrics exist, little is known on their implicit assumptions, what they truly measure, and their limits. In consequence, it is d

Maxime Jacquet, Sara Marcatili, Marie-Laure Gallin-Martel, Jean-Luc Bouly

We are currently conceiving, through (MC) simulation, a multi-channel gamma detector array (TIARA for Time-of-flight Imaging ARrAy) for the online monitoring of protontherapy treatments. By measuring the Time-Of-Flight (TOF) between a beam monitor placed upstream and the Prompt-Gamma (PG) detector, our goal is to reconstruct the PG vertex distribution to det

Stylianos Loukas Vasileiou, Alessandro Previti, William Yeoh

In human-aware planning, a planning agent may need to provide an explanation to a human user on why its plan is optimal. A popular approach to do this is called model reconciliation, where the agent tries to reconcile the differences in its model and the human's model such that the plan is also optimal in the human's model. In this paper, we present a logic-

Mireille Louys, Katharina Lutz, Yelena Stein, Anais Egner

Enhancing interoperable data access to radio data has become a science priority within the International Virtual Observatory Alliance (IVOA). This lead to the foundation of the IVOA Radio astronomy Interest Group. Several radio astronomers and project scientists enrolled in various projects (NRAO, ASKAP, LOFAR, JIVE, ALMA, SKA, INAF, NenuFAR, etc.) have join

Shubhankar Gahlot, Junqi Yin, Mallikarjun Shankar

Distributed training in deep learning (DL) is common practice as data and models grow. The current practice for distributed training of deep neural networks faces the challenges of communication bottlenecks when operating at scale, and model accuracy deterioration with an increase in global batch size. Present solutions focus on improving message exchange ef

Nikolas P. Breuckmann, Jens N. Eberhardt

This work provides the first explicit and non-random family of $[[N,K,D]]$ LDPC quantum codes which encode $K \in \Theta(N^\frac{4}{5})$ logical qubits with distance $D \in \Omega(N^\frac{3}{5})$. The family is constructed by amalgamating classical codes and Ramanujan graphs via an operation called balanced product. Recently, Hastings-Haah-O'Donnell and Pant

Şirag Erkol, Filippo Radicchi

We consider two large datasets consisting of all games played among top-tier European soccer clubs in the last 60 years, and among professional American basketball teams in the past 70 years. We leverage game data to build networks of pairwise interactions between the head coaches of the teams, and measure their career performance in terms of network central

Ching Jin, Yifang Ma, Brian Uzzi

Fast growing scientific topics have famously been key harbingers of the new frontiers of science, yet, large-scale analyses of their genesis and impact are rare. We investigate one possible factor connected with a topic's extraordinary growth: scientific prizes. Our longitudinal analysis of nearly all recognized prizes worldwide and over 11,000 scientific to

R. Krause, S. Aeschlimann, M. Chavez-Cervantes, R. Perea-Causin

Van-der-Waals heterostructures show many intriguing phenomena including ultrafast charge separation following strong excitonic absorption in the visible spectral range. However, despite the enormous potential for future applications in the field of optoelectronics, the underlying microscopic mechanism remains controversial. Here we use time- and angle-resolv

Homayoun Valafar, Faramarz Valafar

Analysis of 1H-NMR spectra is often hindered by large variations that occur during the collection of these spectra. Large solvent and standard peaks, base line drift and negative peaks (due to improper phasing) are among some of these variations. Furthermore, some instrument dependent alterations, such as incorrect shimming, are also embedded in the recorded

O. V. Kliushnichenko, S. P. Lukyanets

The perturbation of a medium field (a particle wake) determines the Stokes drag on the particle itself. Besides, it affects the motion of other particles, inducing non-equilibrium correlations between them. We study the induced non-equilibrium correlations and forces, acting on constituent particles of the bunch or cluster of impurities exposed to a gas stre

M. Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin

Applications such as simulating complicated quantum systems or solving large-scale linear algebra problems are very challenging for classical computers due to the extremely high computational cost. Quantum computers promise a solution, although fault-tolerant quantum computers will likely not be available in the near future. Current quantum devices have seri

Benjamin Ramtoula, Adam Caccavale, Giovanni Beltrame, Mac Schwager

Determining the relative position and orientation of objects in an environment is a fundamental building block for a wide range of robotics applications. To accomplish this task efficiently in practical settings, a method must be fast, use common sensors, and generalize easily to new objects and environments. We present MSL-RAPTOR, a two-stage algorithm for

Sidharth Singla

Checking and confirming factual information in texts and speeches is vital to determine the veracity and correctness of the factual statements. This work was previously done by journalists and other manual means but it is a time-consuming task. With the advancements in Information Retrieval and NLP, research in the area of Fact-checking is getting attention

Imran Sultan, Nicholas Frontiere, Salman Habib, Katrin Heitmann

This paper introduces SMACC -- Subhalo Mass-loss Analysis using Core Catalogs. SMACC adds a mass model to substructure merger trees based on halo "core tracking." Our approach avoids the need for running expensive subhalo finding algorithms and instead uses subhalo mass-loss modeling to assign masses to halo cores. We present details of the SMACC methodology

William Golding, Sam Krupa, Alexis Vasseur

In this paper, we study the $a$-contraction property of small extremal shocks for 1-d systems of hyperbolic conservation laws endowed with a single convex entropy, when subjected to large perturbations. We show that the weight coefficient $a$ can be chosen with amplitude proportional to the size of the shock. The main result of this paper is a key building b

Guillermo Cortiñas, Santiago Vega

Let $\ell$ be a commutative ring with involution $*$ containing an element $\lambda$ such that $\lambda+\lambda^*=1$ and let $\operatorname{Alg}^*_\ell$ be the category of $\ell$-algebras equipped with a semilinear involution and involution preserving homomorphisms. We construct a triangulated category $kk^h$ and a functor $j^h:\operatorname{Alg}^*_\ell\to k

Ajinkya Tejankar, Soroush Abbasi Koohpayegani, Vipin Pillai, Paolo Favaro

Recently, contrastive learning has achieved great results in self-supervised learning, where the main idea is to push two augmentations of an image (positive pairs) closer compared to other random images (negative pairs). We argue that not all random images are equal. Hence, we introduce a self supervised learning algorithm where we use a soft similarity for

Samuel Ackerman, Eitan Farchi, Orna Raz, Marcel Zalmanovici

A trained ML model is deployed on another `test' dataset where target feature values (labels) are unknown. Drift is distribution change between the training and deployment data, which is concerning if model performance changes. For a cat/dog image classifier, for instance, drift during deployment could be rabbit images (new class) or cat/dog images with chan

Haonan Huang, Jacob Senkpiel, Ciprian Padurariu, Robert Drost

Magnetic impurities on superconductors induce discrete bound levels inside the superconducting gap, known as Yu-Shiba-Rusinov (YSR) states. YSR levels are fully spin-polarized such that the tunneling between YSR states depends on their relative spin orientation. Here, we use scanning tunneling spectroscopy to resolve the spin dynamics in the tunneling proces

Homayoun Valafar, Okan K. Ersoy, Farmaraz Valafar

Parallel implementations of distributed global optimization (DGO) [13] on MP-1 and NCUBE parallel computers revealed an approximate O(n) increase in the performance of this algorithm. Therefore, the implementation of the DGO on parallel processors can remedy the only draw back of this algorithm which is the O(n2) of execution time as the number of the dimens

Christian Reiher, Vojtěch Rödl, Marcelo Sales, Kevin Sames

For integers $k\ge 2$ and $N\ge 2k+1$ there are $k!2^k$ canonical orderings of the edges of the complete $k$-uniform hypergraph with vertex set $[N] = \{1,2,\dots, N\}$. These are exactly the orderings with the property that any two subsets $A, B\subseteq [N]$ of the same size induce isomorphic suborderings. We study the associated canonisation problem to es

Ioannis Dalianis, Chris Kouvaris

We calculate the gravitational wave background produced from density perturbations in an early matter domination era where primordial black holes form. The formation of black holes requires perturbations out of the linear regime. Space with such perturbations reach a maximum expansion before it collapses asymmetrically forming a Zel'dovich pancake which depe

CMS Collaboration

Measurements of the total and differential fiducial cross sections for the Z boson decaying into two neutrinos are presented at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV. The data were collected by the CMS detector in 2016 and correspond to an integrated luminosity of 35.9 fb$^{-1}$. In these measurements, events are selected c

Dominik Rist, Christian Saemann, Miro van der Worp

We present a six-dimensional $\mathcal{N}=(1,0)$ supersymmetric higher gauge theory in which self-duality is consistently implemented by physically trivial additional fields. The action contains both $\mathcal{N}=(1,0)$ tensor and vector multiplets and is non-trivially interacting. The tensor multiplet part is loosely related to a recently proposed action by

Homayoun Valafar, Okan K. Ersoy, Faramarz Valafar

A new technique of global optimization and its applications in particular to neural networks are presented. The algorithm is also compared to other global optimization algorithms such as Gradient descent (GD), Monte Carlo (MC), Genetic Algorithm (GA) and other commercial packages. This new optimization technique proved itself worthy of further study after ob

Qi Wang, Philipp Reiter, Detlef Lohse, Olga Shishkina

Penetrative turbulence, which occurs in a convectively unstable fluid layer and penetrates into an adjacent, originally stably stratified layer, is numerically and theoretically analyzed. We chose the most relevant example, namely thermally driven flow of water with a temperature around $T_m\approx 4^\circ\rm{C}$, where it has its density maximum. We pick th

Abdullah Sarhan, Jon Rokne, Reda Alhajj, Andrew Crichton

The vascular structure of blood vessels is important in diagnosing retinal conditions such as glaucoma and diabetic retinopathy. Accurate segmentation of these vessels can help in detecting retinal objects such as the optic disc and optic cup and hence determine if there are damages to these areas. Moreover, the structure of the vessels can help in diagnosin

Sebastian Ehlert, Uwe Huniar, Jinliang Ning, James W. Furness

We combine a regularized variant of the strongly constrained and appropriately normed semilocal density functional [J. Sun, A. Ruzsinszky, and J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015)] with the latest generation semi-classical London dispersion correction. The resulting density functional approximation r2SCAN-D4 has the speed of generalized gradient

Gleb A. Egorov, George V. Eleftheriades

In this publication we continue our previous work on extending the angular scan range of phased arrays using metasurfaces. We consider in detail scan enhancement using a single metasurface lens in the near-field of a source and provide analytical expressions for source excitation to obtain a desired beam. We show that such a device suffers from the same dire

Martin Reinhardt, Neil J. Bruce, Daria B. Kokh, Rebecca C. Wade

Simulations of macromolecular diffusion and adsorption in confined environments can offer valuable mechanistic insights into numerous biophysical processes. In order to model solutes at atomic detail on relevant time scales, Brownian Dynamics simulations can be carried out with the approximation of rigid body solutes moving through a continuum solvent. This

Xiangyu Ni, Bill Goodwine

This paper proposes a method to quickly and efficiently compute the voltage and current along a transmission line which can be "damaged"; that is its electrical properties can be unevenly distributed. The method approximates a transmission line by a self-similar circuit network and leverages our previous work regarding the frequency response for that class o

Peter L. Cohen, Colin B. Fogarty

In randomized experiments, adjusting for observed features when estimating treatment effects has been proposed as a way to improve asymptotic efficiency. However, only linear regression has been proven to form an estimate of the average treatment effect that is asymptotically no less efficient than the treated-minus-control difference in means regardless of

V. M. G. Silveira, C. A. Z. Vasconcellos, E. G. S. Luna, D. Hadjimichef

We investigate non-inertial effects on $CP$-violating processes using a model, based on the framework of quantum field theory in curved spacetimes, devised to account for the decay of accelerated particles. We show that the $CP$ violation parameter for the decay of accelerated kaons into two pions decreases very slightly as very high accelerations are achiev

Sean Oesch, Rob Gillen, Tom Karnowski

While collaboration among data scientists is a key to organizational productivity, data analysts face significant barriers to achieving this end, including data sharing, accessing and configuring the required computational environment, and a unified method of sharing knowledge. Each of these barriers to collaboration is related to the fundamental question of

Huan Wang, Can Qin, Yulun Zhang, Yun Fu

Regularization has long been utilized to learn sparsity in deep neural network pruning. However, its role is mainly explored in the small penalty strength regime. In this work, we extend its application to a new scenario where the regularization grows large gradually to tackle two central problems of pruning: pruning schedule and weight importance scoring. (

Ran Cheng, Christopher Agia, Yuan Ren, Xinhai Li

With the increasing reliance of self-driving and similar robotic systems on robust 3D vision, the processing of LiDAR scans with deep convolutional neural networks has become a trend in academia and industry alike. Prior attempts on the challenging Semantic Scene Completion task - which entails the inference of dense 3D structure and associated semantic labe

Gary P. T. Choi, Levi H. Dudte, L. Mahadevan

Kirigami involves cutting a flat, thin sheet that allows it to morph from a closed, compact configuration into an open deployed structure via coordinated rotations of the internal tiles. By recognizing and generalizing the geometric constraints that enable this art form, we propose a design framework for compact reconfigurable kirigami patterns, which can mo

Claudio Bombardelli, Gabriele Falco, Davide Amato, Aaron J. Rosengren

With the upcoming launch of large constellations of satellites in the low-Earth orbit (LEO) region it will become important to organize the physical space occupied by the different operating satellites in order to minimize critical conjunctions and avoid collisions. Here, we introduce the definition of space occupancy as the domain occupied by an individual

Angeli Sandoval, Gabriella Contardo, Trevor J. David

There is growing evidence that the population of close-in planets discovered by the Kepler mission was sculpted by atmospheric loss, though the typical timescale for this evolution is not well-constrained. Among a highly complete sample of planet hosts of varying ages the age-dependence of the relative fraction of super-Earth and sub-Neptune detections can b

Earl T. Campbell

Simulation of the Hubbard model is a leading candidate for the first useful applications of a fault-tolerant quantum computer. A recent study of quantum algorithms for early simulations of the Hubbard model [Kivlichan \textit{et al.} Quantum 4 296 (2019)] found that the lowest resource costs were achieved by split-operator Trotterization combined with the fa

Biagio Brattoli, Uta Buechler, Michael Dorkenwald, Philipp Reiser

Motor behaviour analysis is essential to biomedical research and clinical diagnostics as it provides a non-invasive strategy for identifying motor impairment and its change caused by interventions. State-of-the-art instrumented movement analysis is time- and cost-intensive, since it requires placing physical or virtual markers. Besides the effort required fo

Savas Delikanli, Onur Erdem, Furkan Isik, Hameed Dehghanpour Baruj

Optical gain in solution, which provides high photostability as a result of continuous regeneration of the gain medium, is extremely attractive for optoelectronic applications. Here, we propose and demonstrate amplified spontaneous emission (ASE) in solution with ultralow thresholds of 30 mikroJ/cm2 in red and of 44 mikroJ/cm2 in green from engineered colloi

Mehdi Bahri, Eimear O' Sullivan, Shunwang Gong, Feng Liu

Standard registration algorithms need to be independently applied to each surface to register, following careful pre-processing and hand-tuning. Recently, learning-based approaches have emerged that reduce the registration of new scans to running inference with a previously-trained model. In this paper, we cast the registration task as a surface-to-surface t

Xiangyu Ni, Bill Goodwine

In this paper, we propose a method to identify the damaged component and quantify its damage amount in a large network given its overall frequency response. The identification procedure takes advantage of our previous work which exactly models the frequency response of that large network when it is damaged. As a result, the test shows that our method works w

A. Beckert, R. I. Hermans, M. Grimm, J. R. Freeman

We use complementary optical spectroscopy methods to directly measure the lowest crystal-field energies of the rare-earth quantum magnet LiY$_{1-x}$Ho$_{x}$F$_{4}$, including their hyperfine splittings, with more than 10 times higher resolution than previous work. We are able to observe energy level splittings due to the $^6\mathrm{Li}$ and $^7\mathrm{Li}$ i

Jesslyn Alekseyev, Erica Dixon, Vilhelm L Andersen Woltz, Danny Weitzner

By using modern cryptographic techniques, privacy-preserving Automated Exposure Notification (AEN) technologies offer the promise of mitigating disease spread by automatically recording contacts between people over the incubation period while maintaining individual data privacy. Today, public health departments in States and other countries around the world

Soran Jahangiri, Juan Miguel Arrazola, Alain Delgado

An accurate description of electron transport at a molecular level requires a precise treatment of quantum effects. These effects play a crucial role in determining the electron transport properties of single molecules, such as current-voltage curves, which can be challenging to simulate classically. Here we introduce a quantum algorithm to efficiently calcu

Stefano Cipolla, Jacek Gondzio

Embedding randomization procedures in the Alternating Direction Method of Multipliers (ADMM) has recently attracted an increasing amount of interest as a remedy to the fact that the direct multi-block generalization of ADMM is not necessarily convergent. Even if, in practice, the introduction of such techniques could \textit{mitigate} the diverging behaviour

Henri M. J. Boffin, Jakob Vinther, Lars K. Lundin, Gurvan Bazin

Users of the La Silla Paranal Observatory have to rely on the ESO Exposure Time Calculator (ETC) to prepare their observations. A project has been started at ESO to modernise the ETC, based on a python backend and an angular-based front-end. The ETC 2.0 will have a programmatic interface to enable the results to be included in an automated quality control lo

Alexander Lalejini, Matthew Andres Moreno, Charles Ofria

We introduce and experimentally demonstrate the utility of tag-based genetic regulation, a new genetic programming (GP) technique that allows programs to dynamically adjust which code modules to express. Tags are evolvable labels that provide a flexible mechanism for referencing code modules. Tag-based genetic regulation extends existing tag-based naming sch

Spencer A. Hill, Natalie J. Burls, Alexey Fedorov, Timothy M. Merlis

CO$_2$-forced surface warming in general circulation models (GCMs) is initially polar-amplified in the Arctic but not Antarctic -- a largely hemispherically antisymmetric signal. Nevertheless, we show in CESM1 and eleven LongRunMIP GCMs that the hemispherically symmetric component of global-mean-normalized, zonal-mean warming ($T^*_\mathrm{sym}$) under 4\(\t

H. M. J. Boffin, F. Derie, A. Manescau, R. Siebenmorgen

The FORS Upgrade project (FORS-Up) aims at bringing a new life to the highly demanded workhorse instrument attached to ESO's Very Large Telescope (VLT). FORS2 is a multimode optical instrument, which started regular science operations in 2000 and since then, together with its twin, FORS1, has been one of the most demanded and most productive instruments of t

Jiening Zhu, Kaiming Xu, Allen Tannenbaum

Vector-valued Gaussian mixtures form an important special subset of vector-valued distributions. In general, vector-valued distributions constitute natural representations for physical entities, which can mutate or transit among alternative manifestations distributed in a given space. A key example is color imagery. In this note, we vectorize the Gaussian mi

CMS Collaboration

The first measurement of the inclusive cross section for top quark pairs ($\mathrm{t\bar{t}}$) produced in association with two additional charm jets is presented. The analysis uses the dileptonic final states of $\mathrm{t\bar{t}}$ events produced in proton-proton collisions at a centre-of-mass energy of 13 TeV. The data correspond to an integrated luminosi

Marc Bataille

We start by studying the subgroup structures underlying stabilizer circuits. Then we apply our results to provide two normal forms for stabilizer circuits. These forms are computed by induction using simple conjugation rules in the Clifford group and our algorithms do not rely on a special decomposition in the symplectic group. The first normal form has shap

V. A Khlebnikov, V. V Tsyganok, D. A. Pershin, E. T Davletov

Recent studies demonstrated anomalous temperature shifts for some Fano-Feshbach resonances of thulium atoms. These anomalies were explained by the variation in light intensity in the optical dipole trap, which accompanied changes in temperature. In addition, a temperature-related transformation of the statistics of the interresonance spacing was demonstrated

Xinzhe Fu, Eytan Modiano

Network Utility Maximization (NUM) studies the problems of allocating traffic rates to network users in order to maximize the users' total utility subject to network resource constraints. In this paper, we propose a new NUM framework, Learning-NUM, where the users' utility functions are unknown apriori and the utility function values of the traffic rates can

Yucel Aydin, Gunes Karabulut Kurt, Enver Ozdemir, Halim Yanikomeroglu

The widespread use of new technologies such as the Internet of things (IoT) and machine type communication(MTC) forces an increase on the number of user equipments(UEs) and MTC devices that are connecting to mobile networks. Inherently, as the number of UEs inside a base station's (BS) coverage area surges, the quality of service (QoS) tends to decline. The

Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran

Contextual bandits algorithms have become essential in real-world user interaction problems in recent years. However, these algorithms rely on context as attribute value representation, which makes them unfeasible for real-world domains like social networks are inherently relational. We propose Relational Boosted Bandits(RB2), acontextual bandits algorithm f

Michael Fleermann, Werner Kirsch, Gabor Toth

In this paper, we propose a new interpretation of local limit theorems for univariate and multivariate distributions on lattices. We show that - given a local limit theorem in the standard sense - the distributions are approximated well by the limit distribution, uniformly on intervals of possibly decaying length. We identify the maximally allowable decay sp

M. Ángeles Pérez-García, J. Silk

Neutron Stars (NSs) are compact stellar objects that are stable solutions in General Relativity. Their internal structure is usually described using an equation of state that involves the presence of ordinary matter and its interactions. However there is now a large consensus that an elusive sector of matter in the Universe, described as dark matter, remains

John M. Martinis

When working to understand quantum systems engineering, there are many constraints to building a scalable quantum computer. Here I discuss a constraint on the qubit control system from an information point of view, showing that the large amount of information needed for the control system will put significant constraints on the control system. The size the q

Peter J. Rodenkirch, Thomas Rometsch, Cornelis P. Dullemond, Philipp Weber

High resolution ALMA observations revealed a variety of rich substructures in numerous protoplanetary disks. These structures consist of rings, gaps and asymmetric features. It is debated whether planets can be accounted for these substructures in the dust continuum. Characterizing the origin of asymmetries as seen in HD 163296 might lead to a better underst

Te-Lin Wu, Shikhar Singh, Sayan Paul, Gully Burns

We introduce a new dataset, MELINDA, for Multimodal biomEdicaL experImeNt methoD clAssification. The dataset is collected in a fully automated distant supervision manner, where the labels are obtained from an existing curated database, and the actual contents are extracted from papers associated with each of the records in the database. We benchmark various

Jun Jiang, David Grass, Yue Zhou, Warren S. Warren

Pump-probe microscopy is an emerging nonlinear imaging technique based on high repetition rate lasers and fast intensity modulation. Here we present new methods for pump-probe microscopy that keep the beam intensity constant and instead modulate the inter-pulse time delay, the relative polarization, or the pulse length. These techniques can improve image qua

Robert A. Bridges, Sean Oesch, Miki E. Verma, Michael D. Iannacone

In this paper, we present a scientific evaluation of four prominent malware detection tools to assist an organization with two primary questions: To what extent do ML-based tools accurately classify previously- and never-before-seen files? Is it worth purchasing a network-level malware detector? To identify weaknesses, we tested each tool against 3,536 total

Christian W. Bauer, Aneesh V. Manohar, Pier Francesco Monni

The resummation of radiative corrections to collider jet observables using soft collinear effective theory is encoded in differential renormalization group equations (RGEs), with anomalous dimensions depending on the observable under consideration. This observable dependence arises from the ultraviolet (UV) singular structure of real phase space integrals in

Xiangyu Ni, Bill Goodwine

In this paper, we propose that a tree-like network with damage can be modeled as the product of a fractional-order nominal plant and a fractional-order multiplicative disturbance, which is well structured and completely characterized by the damage amount at each damaged component. Such way of modeling brings us insights about that damaged network's behavior,

Mathew Calkins, S. James Gates, Caroline Klivans

Beginning from a discussion of the known most fundamental dynamical structures of the Standard Model of physics, extended into the realms of mathematics and theory by the concept of "supersymmetry" or "SUSY," an introduction to efforts to develop a complete representation theory is given. Techniques drawing from graph theory, coding theory, Coxeter Groups, R

Jan Behrends, Benjamin Béri

The Sachdev-Ye-Kitaev (SYK) model is an all-to-all interacting Majorana fermion model for many-body quantum chaos and the holographic correspondence. Here we construct fermionic all-to-all Floquet quantum circuits of random four-body gates designed to capture key features of SYK dynamics. Our circuits can be built using local ingredients in Majorana devices,